README.md

Getting started

Try it out on Binder ☝️ or follow the steps below 👇 to run locally.

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Check that your active Python environment has the dependencies listed in environment.yml. Otherwise, you can create a new environment using:

conda env create -f environment.yml

And then activate it using:

conda activate canopy-app

The primary function is run(), which runs canopy-app and returns an xarray Dataset. By default, it runs the default case.

from canopy_app import run

ds = run()

You can override default namelist options by passing a dictionary to run().

# Point setup
ds = run(
    config={
        "filenames": {"file_vars": "../input/input_variables_point.txt"},
        "userdefs": {"infmt_opt": 1, "nlat": 1, "nlon": 1},
    },
)

There are also helper functions for running sets of experiments with different namelist options.

# Multiple point setup cases
from canopy_app import config_cases, run_config_sens

cases = config_cases(
    file_vars="../input/input_variables_point.txt",
    infmt_opt=1,
    nlat=1,
    nlon=1,
    z0ghc=[0.001, 0.01],
    lambdars=[1.0, 1.25],
    product=True,  # 4 cases if true, 2 if false
)
ds = run_config_sens(cases)

☝️ We still get a single output dataset, but it has a case dimension.

Generating global data

You can also download and generate global gridded canopy-app inputs using Python.

1. Edit python script (global_data_process.py)

2. Change user settings

   '''User Options'''
   path     = '/scratch/pcampbe8/canopy-app/input'  # work directory
   year     = 2022   # year
   month    = 7      # month
   day      = 1      # day
   houri    = 12     # gfs initialization hour in UTC (caution currently GFS files are initialized at 12 UTC only -- do not change)
   hour     = 00     # gfs forecast hour in UTC
   ref_lev  = 10     # reference height above the canopy (m)
   frp_src  = 1      # frp data source (0: local source; 1: check local source first, switch to climatological file if no available data; 2: 12 month climatology; 3: all ones when ifcanwaf=.FALSE.)

3. Activate canopy-app Conda environment:

   conda activate canopy-app
   

4. Run Python script

   python global_data_process.py